Reverse Dependencies of mne

The following projects have a declared dependency on mne:

• agcounts — This project contains code to generate activity counts from accelerometer data.
• alice-ml — ALICE - Automated Labeling of Independent Components for EEG
• alphacsc — Convolutional dictionary learning for noisy signals.
• alphawaves — Alpha Waves Dataset
• amanda-rerp-ols — An extension of mne.stats.linear_regression
• AMANDA047 — Packaging rerp_package
• asrpy — Artifact Subspace Reconstruction in Python.
• asrpy-eh — Artifact Subspace Reconstruction in Python.
• automatic-spike-detection — Python library for automatically detecting interictal epileptiform discharges (IEDs) by means of nonnegative matrix factorization (NMF)
• autoreject — Automated rejection and repair of epochs in M/EEG.
• batch22 — batch22 (b22)
• bci-dataset — Building HDF datasets for machine learning.
• bci4als — A complete EEG Motor Imagery Classification pipeline
• bcipy — Python Software for Brain-Computer Interface.
• benchnirs — Benchmarking framework for machine learning with fNIRS
• BiModNeuroCNN — Tools for bimodal training of CNNs, i.e. concurrent training with two data types
• biopsykit — A Python package for the analysis of biopsychological data.
• Biosip-Tools — Tools for Biosip Group
• biotuner — Time series harmonic analysis for adaptive tuning systems and microtonal exploration
• BIpy — py for BI
• blockmatrix — Utilities to handle blockmatrices, especially covariance matrices.
• borsar — tools for electrophysiological analysis, especially cluster-based tests.
• brain-pipe — Brain Pipe
• Braindecode — Deep learning software to decode EEG, ECG or MEG signals
• Brainfeatures — A toolbox to decode raw time-domain EEG using features.
• brainsight — Analysis toolkit for brain activity data.
• brainviewer — A brain viewer in Python.
• bsl — Real-time framework for online neuroscience research through LSL-compatible devices.
• CardioPy — Analysis package for single-lead clinical EKG data
• clamnibs — Analysis of closed-loop amplitude-modulated non-invasive brain stimulation experiments
• cloudbrain — Platform for wearable data analysis.
• Clumsy — A collection of scripts used in the Computational Memory Lab for timeseries analysis
• cmb — Cere-MEG-Bellum (CMB) - Cerbellum segmentation and forward solution calculation
• cmne — Contextual Minimum Norm Estimates (CMNE)
• cognify — DataScience environment for Insai BCI
• cohort-creator — Creates a neuroimaging cohort by aggregating data across datasets.
• deepsleep — Sleep EEG classification
• easyEEG — Concise, agile, and flexible EEG toolbox
• eeg-emotion-recognition — no summary
• eeg_eyetracking_parser — A Python module for reading concurrently recorded EEG and eye-tracking data,
• eeg-positions — Compute and plot standard EEG electrode positions.
• eeg-to-fmri — no summary
• eegain — EEG emotion recognition package for standardization
• eegbase-nix-converter — EEGbase -> NIX converter converts BranVision/odML dataset to a NIX container file
• eeghdf — eeghdf is a module for reading a writing EEG data into the hdf5 format
• eegio — EEGIO: An io package for eeg data that is MNE-Python and MNE-BIDS compatible .
• EEGraph — no summary
• eegyolk — A package for analysis of EEG data
• eelbrain — MEG/EEG analysis tools
• EmBCI — no summary
• ephypype — Python package providing pipelines for electrophysiological (EEG/MEG) data within nipype framework.
• ephys-anonymizer — ephys_anonymizer: Use the Viola-Jones algorithm to anonymize faces with a black box and anonymize electrophysiology data with mne-python
• ephysvibe — .
• esdap — Epileptic Seizure Detection and Prediction from EEG data
• ESINet — Solves the M/EEG inverse problem using artificial neural networks with Python 3 and the MNE library.
• esppy — EEG Signal Processing Library
• ethome — ethome - a package for multimodal behavioural recordings
• evaler — Evaler.
• ExBrainable — ExBrainable: An Open-Source GUI for CNN-based EEG Decoding and Model Interpretation
• explorepy — Python API for Mentalab biosignal aquisition devices
• eyelinkio — A lightweight library for reading Eyelink Data Format files in Python.
• ezdsp — Easy digital signal processing
• finnpy — Toolbox for the analysis of electrophysiological data
• freq-tag — A Python package facilitating the analysis of frequency-tagging data
• frites — Framework of Information Theory for Electrophysiological data and Statistics
• fw-file — Unified data-file interface
• fw-gear-file-metadata-importer — Extract metadata of input file to Flywheel.
• gcpds-mi — no summary
• gcpds-utils — no summary
• gcpds-visualizations — no summary
• happyfeat — ex. package for HappyFeat
• HFODetector — Package for detecting HFOs
• hmp — Package for fitting Hidden Multivariate pattern model to time-series
• hsmm-mvpy — DEPRECATED new name under HMP, see https://pypi.org/project/hmp/
• hu-neuro-pipeline — Single trial EEG pipeline at the Abdel Rahman Lab for Neurocognitive Psychology, Humboldt-Universität zu Berlin
• hypnos — Tools related to sleep research
• HyPyP — The Hyperscanning Python Pipeline.
• IFReject — Isolation_Forest_Automatic_Rejection
• img-pipe — Image processing pipeline for localization and identification of electrodes for electrocorticography
• invertmeeg — A high-level M/EEG Python library for EEG inverse solutions
• karaone — A simple utils tools for kara ona database eeg
• laura — **laura**: Local Auto-Regressive Average
• lmsleepdata — a python analyse tool for LM Data Recorder data
• LongTermBiosignals — Python library for easy managing and processing of large Long-Term Biosignals.
• meeg-tools — EEG/MEEG data preprocessing and analyses tools
• meeglet — Morlet Wavelets for M/EEG analysis
• meggie-sourceanalysis — no summary
• metabci — A Library of Datasets, Algorithms, and Experiments workflow for Brain-Computer Interface
• micromed-io — A library to read, emulate, and forward Micromed data in standard formats
• mindpype — A library for building BCI data processing pipelines.
• misst — Automated murine polysomnogram sleep staging for Python.
• mne-bids — MNE-BIDS: Organizing MEG, EEG, and iEEG data according to the BIDS specification and facilitating their analysis with MNE-Python
• mne-bids-pipeline — A full-flegded processing pipeline for your MEG and EEG data
• mne-connectivity — mne-connectivity: A module for connectivity data analysis with MNE.
• mne-faster — Code for performing the FASTER pipeline on MNE-Python data structures.
• mne-features — MNE-Features software for extracting features from multivariate time series
• mne-gui-addons — MNE-Python GUI addons.
• mne-hfo — MNE-HFO: Facilitates estimation/detection of high-frequency oscillationevents on iEEG data with MNE-Python, MNE-BIDS and scikit-learn.
• mne-icalabel — MNE-ICALabel: Automatic labeling of ICA components from MEG, EEG and iEEG data with MNE.
• mne-kit-gui — A module for KIT MEG coregistration.